The functions of transcription factors depend upon correct recognition of target DNA sites in promotor and enhancer regions. Although intensive research has been done to study their interactions, many questions remain. One of them is how conserved DNA binding motif mediates recognition of divergent DNA sites. The hepatocyte nuclear factor 3 (HNF-3) and Drysophila forkhead (fkh) related proteins (HFH) constitute a large family of proteins and use a modified helix turn known as the "winged helix" motif to recognize their target DNA sites. Although the HFH proteins have almost invariable recognition sequences, they exhibit divergent DNA binding specificity. This cannot be explained by the model of specific interactions between conserved amino acids and DNA bases. Based on biochemical data, a hypothesis is proposed that DNA binding specificity of the HFH-3/fkh homologues is mediated by different presentation of the DNA recognition helix. To test this hypothesis in detail, we propose to apply both molecular biology and modern heteronuclear NMR methods to study the structures and the DNA binding specificity of HFH-1 and HFH-2: two divergent HFH family members. We will determine and compare the structures of the DNA binding domains of HFH-1 and HFH-2. We seek to understand the effect of the 20 amino acid sequence on structural presentation of the recognition sequence. We will compare the structures of the DNA complexes of HFH-1 and HFH-2 and study whether the same amino acid residues in the HFH proteins interact with DNA. We will also study the dynamics properties of the HFH proteins and their DNA complexes. We are particularly interested in the DNA contact residues and the dynamic wing sequence in the C-terminus. We will study the effect of mutations designed to alter presentation of the recognition helix on DNA binding specificity. The initial target will be a 20 amino acid region adjacent to the recognition sequence, which influences the DNA binding specificity of the HFH proteins. The study of protein-DNA interactions is not only important for understanding transcription and gene regulation, but is also critical for molecular modeling and protein design.